2026-06-29T07:52:23Zhttps://docta.ucm.es/rest/oai/request

oai:docta.ucm.es:20.500.14352/176582024-09-23T16:59:28Zcom_20.500.14352_14col_20.500.14352_15

Learning Principal Component Analysis by Using Data from Air Quality Networks Pérez Arribas, Luis Vicente León González, María Eugenia de Rosales Conrado, Noelia 543 Graduate Education/Research Upper-Division Undergraduate Environmental Chemistry Computer-Based Learning Chemometrics Química analítica (Química) 2301 Química Analítica With the final objective of using computational and chemometrics tools in the chemistry studies, this paper shows the methodology and interpretation of the Principal Component Analysis (PCA) using pollution data from different cities. This paper describes how students can obtain data on air quality and process such data for additional information related to the pollution sources, climate effects, and social aspects over pollution levels by using a powerful chemometrics tool such as principal component analysis (PCA). The paper could also be useful for students interested in environmental chemistry and pollution interpretation; this statistical method is a simple way to display visually as much as possible of the total variation of the data in a few dimensions, and it is an excellent tool for looking into the normal pollution patterns. Depto. de Química Analítica Fac. de Ciencias Químicas TRUE pub 2023-06-17T21:51:20Z 2023-06-17T21:51:20Z 2017-01 journal article https://hdl.handle.net/20.500.14352/17658 0021-9584 10.1021/acs.jchemed.6b00550 eng restricted access application/pdf ACS